Description
Predict problems and recommend proactive maintenance for power generation and supporting equipment
Benefits & ROI
1.6
Linked Case Studies
Case Study
Large European integrated electric power company
A large european integrated electric power company is predicting, diagnosing and reducing equipment failures in conventional power plants with machine learning
Case Study
London Fire Brigade
The London Fire Brigade identifies the areas prone to fires in ducting systems to provide targeted maintenance using natural language processing
Case Study
Rice University
Rice University researchers improve on the state-of-the-art for wind turbine icing detection with a CNN
Case Study
Enel
Enel is reducing operational and capital expenses by predicting maintenance and improving asset performance using machine learning
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Source: mckinsey.com · Editor: original-sdg